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Lipochitooligosaccharide (LCO) perception by legumes is required to establish symbiotic relationships with nitrogen fixing bacteria. Here the authors show that nutrient starvation can activate LCO perception in cereals to promote symbiotic association with arbuscular mycorrhizal fungi.

Chloroplast development and brassinosteroid (BR) signaling both regulate plant photomorphogenesis. Here the authors show that DAY, a DnaJ-like domain-containing membrane protein, regulates both processes by binding and stabilizing both BRI1, the BR receptor, and POR, a key enzyme in chlorophyll biosynthesis.

Signaling via the D14L karrikin receptor conditions rice roots for association with arbuscular mycorrhizal fungi. Here, Choi et al. show that SMAX1, a rice homolog of an Arabidopsis repressor of karrikin signaling, acts downstream of D14L to suppress mycorrhizal symbiosis and strigolactone biosynthesis.

Polysaccharide molecules chitooligosaccharides (COs) and peptidoglycan not only activate plant immunity but also trigger plant symbiosis signalling. Here the authors show that a combination of COs and lipochitooligosaccharides (LCOs) act synergistically to suppress immunity and promote symbiosis to facilitate beneficial fungal associations.

Cultivated barley (Hordeum vulgare L.) is one of the most produced cereal crops worldwide after maize, bread wheat, and rice. Barley is an important crop species not only as a food source, but also in plant genetics because it harbors numerous stress response alleles in its genome that can be exploited for crop engineering. However, the functional annotation of its genome is relatively poor compared with other major crops. Moreover, bioinformatics tools for system-wide analyses of omics data from barley are not yet available. We have thus developed BarleyNet, a co-functional network of 26,145 barley genes, along with a web server for network-based predictions (http://www.inetbio.org/barleynet). We demonstrated that BarleyNet's prediction of biological processes is more accurate than that of an existing barley gene network. We implemented three complementary network-based algorithms for prioritizing genes or functional concepts to study genetic components of complex traits such as environmental stress responses: (i) a pathway-centric search for candidate genes of pathways or complex traits; (ii) a gene-centric search to infer novel functional concepts for genes; and (iii) a context-centric search for novel genes associated with stress response. We demonstrated the usefulness of these network analysis tools in the study of stress response using proteomics and transcriptomics data from barley leaves and roots upon drought or heat stresses. These results suggest that BarleyNet will facilitate our understanding of the underlying genetic components of complex traits in barley.

Histone post-translational modifications (PTMs) create a powerful regulatory mechanism for maintaining chromosomal integrity in cells. Histone acetylation and methylation, the most widely studied histone PTMs, act in concert with chromatin-associated proteins to control access to genetic information during transcription. Alterations in cellular histone PTMs have been linked to disease states and have crucial biomarker and therapeutic potential. Traditional bottom-up mass spectrometry of histones requires large numbers of cells, typically one million or more. However, for some cell subtype-specific studies, it is difficult or impossible to obtain such large numbers of cells and quantification of rare histone PTMs is often unachievable. An established targeted LC-MS/MS method was used to quantify the abundance of histone PTMs from cell lines and primary human specimens. Sample preparation was modified by omitting nuclear isolation and reducing the rounds of histone derivatization to improve detection of histone peptides down to 1,000 cells. In the current study, we developed and validated a quantitative LC-MS/MS approach tailored for a targeted histone assay of 75 histone peptides with as few as 10,000 cells. Furthermore, we were able to detect and quantify 61 histone peptides from just 1,000 primary human stem cells. Detection of 37 histone peptides was possible from 1,000 acute myeloid leukemia patient cells. We anticipate that this revised method can be used in many applications where achieving large cell numbers is challenging, including rare human cell populations.

Abstract It is still challenging to predict the efficacy of cisplatin-based therapy, particularly in relation to the activation of macroautophagy/autophagy in oral squamous cell carcinoma (OSCC). We studied the effect of selected chromatin remodeling genes on the cisplatin resistance and their interplay with autophagy in 3-dimensional tumor model and xenografts. We analyzed gene expression patterns in the cisplatin-sensitive UMSCC1, and a paired cisplatin-resistant UM-Cis cells. Many histone protein gene clusters involved in nucleosome assembly showed significant difference of expression. Gain- and loss-of-function analyses revealed an inverse correlation between cisplatin resistance and HIST1H3D expression, while a positive correlation was observed with HIST3H2A or HIST3H2B expression. In UM-Cis, HIST3H2A- and HIST3H2B-mediated chromatin remodeling upregulates autophagy status, which results in cisplatin resistance. Additionally, knockdown of HIST3H2A or HIST3H2B downregulated autophagy-activating genes via chromatin compaction of their promoter regions. MiTF, one of the key autophagy regulators upregulated in UM-Cis, negatively regulated transcription of HIST1H3D, suggesting an interplay between chromatin remodeling-dependent cisplatin resistance and autophagy. On comparing the staining intensity between cisplatin-sensitive and –insensitive tissues from OSCC patients, protein expression pattern of the selected histone protein genes were matched with the in vitro data. By examining the relationship between autophagy and chromatin remodeling genes, we identified a set of candidate genes with potential use as markers predicting chemoresistance in OSCC biopsy samples.

Background: It is important to study differential inflammatory cellular migration, particularly of eosinophils and neutrophils, in asthma and how this is influenced by environmental stimuli such as allergen exposure and the effects of anti asthma therapy. Methods: We isolated blood neutrophils and eosinophils from 12 atopic asthmatic human volunteers (Group 1 — four Early Allergic Responders unchallenged (EAR); Group 2 — four Early and Late Allergic Responders (LAR) challenged; Group 3 — four EAR and LAR challenged and treated with systemic corticosteroids) using cGMP CD16 CliniMACS. Cells were isolated prior to allergen challenge where applicable, labelled with 99mTc-HMPAO and then re-infused intravenously. The kinetics of cellular influx/efflux into the lungs and other organs were imaged via scintigraphy over 4 h, starting at 5 to 6 h following allergen challenge where applicable. Results: Neutrophils and eosinophils were isolated to a mean (SD) purity of 98.36% (1.09) and 96.31% (3.0), respectively. Asthmatic neutrophils were activated at baseline, mean (SD) CD11bHigh cells 46 (10.50) %. Isolation and radiolabelling significantly increased their activation to >98%. Eosinophils were not activated at baseline, CD69+ cells 1.9 (0.6) %, increasing to 38 (3.46) % following isolation and labelling. Analysis of the kinetics of net eosinophil and neutrophil lung influx/efflux conformed to a net exponential clearance with respective mean half times of clearance 6.98 (2.18) and 14.01 (2.63) minutes for Group 1, 6.03 (0.72) and 16.04 (2.0) minutes for Group 2 and 5.63 (1.20) and 14.56 (3.36) minutes for Group 3. These did not significantly differ between the three asthma groups (p > 0.05). Conclusions: Isolation and radiolabelling significantly increased activation of eosinophils (CD69) and completely activated neutrophils (CD11bHigh) in all asthma groups. Net lung neutrophil efflux was significantly slower than that of eosinophils in all asthma study groups. There was a trend for pre-treatment with systemic corticosteroids to reduce lung retention of eosinophils following allergen challenge.

Recently, nanovaccine-based immunotherapy has been robustly investigated due to its potential in governing the immune response and generating long-term protective immunity. However, the presentation of a tumor peptide-major histocompatibility complex to T lymphocytes is still a challenge that needs to be addressed for eliciting potent antitumor immunity. Type 1 conventional dendritic cell (cDC1) subset is of particular interest due to its pivotal contribution in the cross-presentation of exogenous antigens to CD8+ T cells. Here, the DC-derived nanovaccine (denoted as Si9GM) selectively targets cDC1s with marginal loss of premature antigen release for effective stimulator of interferon genes (STING)-mediated antigen cross-presentation. Bone marrow dendritic cell (BMDC)-derived membranes, conjugated to cDC1-specific antibody (αCLEC9A) and binding to tumor peptide (OVA257-264), are coated onto dendrimer-like polyethylenimine (PEI)-grafted silica nanoparticles. Distinct molecular weight-cargos (αCLEC9A-OVA257-264 conjugates and 2′3′-cGAMP STING agonists) are loaded in hierarchical center-radial pores that enables lysosome escape for potent antigen-cross presentation and activates interferon type I, respectively. Impressively, Si9GM vaccination leads to the upregulation of cytotoxic T cells, a reduction in tumor regulatory T cells (Tregs), M1/M2 macrophage polarization, and immune response that synergizes with αPD-1 immune checkpoint blockade. This nanovaccine fulfills a dual role for both direct T cell activation as an artificial antigen-presenting cell and DC subset maturation, indicating its utility in clinical therapy and precision medicine.

Aim: We assessed the efficacy of anti-hyperkalemic agents for alleviating hyperkalemia and improving clinical outcomes in patients with out-of-hospital cardiac arrest (OHCA). Methods: This was a single-center, retrospective observational study of OHCA patients treated at tertiary hospitals between 2010 and 2020. Adult patients aged 18 or older who were in cardiac arrest at the time of arrival and had records of potassium levels measured during cardiac arrest were included. A linear regression model was used to evaluate the relationship between changes in potassium levels and use of anti-hyperkalemic medications. Cox proportional hazards regression analysis was performed to analyze the relationship between the use of anti-hyperkalemic agents and the achievement of return of spontaneous circulation (ROSC). Results: Among 839 episodes, 465 patients received anti-hyperkalemic medication before ROSC. The rate of ROSC was higher in the no anti-hyperkalemic group than in the anti-hyperkalemic group (55.9 % vs 47.7 %, P = 0.019). The decrease in potassium level in the anti-hyperkalemic group from pre-ROSC to post-ROSC was significantly greater than that in the no anti-hyperkalemic group (coefficient 0.38, 95 % confidence interval [CI], 0.13–0.64, P = 0.003). In Cox proportional hazards regression analysis, the use of anti-hyperkalemic medication was related to a decreased ROSC rate in the overall group (adjusted hazard ratio [aHR] 0.66, 95 % CI, 0.54–0.81, P

Many diverse phenomena in nature often inherently encode both short- and long-term temporal dependencies, which especially result from the direction of the flow of time. In this respect, we discovered experimental evidence suggesting that interrelations of these events are higher for closer time stamps. However, to be able for attention-based models to learn these regularities in short-term dependencies, it requires large amounts of data, which are often infeasible. This is because, while they are good at learning piece-wise temporal dependencies, attention-based models lack structures that encode biases in time series. As a resolution, we propose a simple and efficient method that enables attention layers to better encode the short-term temporal bias of these data sets by applying learnable, adaptive kernels directly to the attention matrices. We chose various prediction tasks for the experiments using Electronic Health Records (EHR) data sets since they are great examples with underlying long- and short-term temporal dependencies. Our experiments show exceptional classification results compared to best-performing models on most tasks and data sets.

Abstract The increasing use of sodium glucose transporter 2 inhibitors (SGLT2i) for treating cardiovascular (CV) diseases and type 2 diabetes (T2D) is accompanied by a rise in euglycemic diabetic ketoacidosis occurrences in cardiac surgery patients. Patients undergoing cardiac surgery, due to their pre-existing CV disease which often requires SGLT2i prescriptions, face an increased risk of postoperative metabolic acidosis (MA) or ketoacidosis (KA) associated with SGLT2i, compounded by fasting and surgical stress. The primary aim of this study is to quantify the incidence of SGLT2i-related postoperative MA or KA and to identify related risk factors. We analyzed data retrospectively of 823 cardiac surgery patients, including 46 treated with SGLT2i from November 2019 to October 2022. Among 46 final cohorts treated preoperatively with SGLT2i, 29 (63%) developed postoperative metabolic complications. Of these 46 patients, stratified into two categories based on postoperative laboratory findings, risk factor analysis were conducted and compared. Analysis indicated a prescription duration over one week significantly elevated the risk of complications (Unadjusted OR, 11.7; p = 0.032*; Adjusted OR, 31.58; p = 0.014*). A subgroup analysis showed that a cardiopulmonary bypass duration of 60 min or less significantly raises the risk of SGLT2i-related postoperative MA in patients with a sufficient prescription duration. We omitted the term "diabetes" in describing complications related to SGLT2i, as these issues are not exclusive to T2D patients. Awareness of SGLT2i-related postoperative MA or KA can help clinicians distinguish between non-life-threatening conditions and severe causes, thereby preventing unnecessary tests and ensuring best practice.

The adverse effects of traffic-related air pollution on children's respiratory health have been widely reported, but few studies have evaluated the impact of traffic-control policies designed to reduce urban air pollution. We assessed associations between traffic-related air pollutants and respiratory/allergic symptoms amongst 8-9 year-old schoolchildren living within the London Low Emission Zone (LEZ). Information on respiratory/allergic symptoms was obtained using a parent-completed questionnaire and linked to modelled annual air pollutant concentrations based on the residential address of each child, using a multivariable mixed effects logistic regression analysis. Exposure to traffic-related air pollutants was associated with current rhinitis: NOx (OR 1.01, 95% CI 1.00-1.02), NO2 (1.03, 1.00-1.06), PM10 (1.16, 1.04-1.28) and PM2.5 (1.38, 1.08-1.78), all per μg/m3 of pollutant, but not with other respiratory/allergic symptoms. The LEZ did not reduce ambient air pollution levels, or affect the prevalence of respiratory/allergic symptoms over the period studied. These data confirm the previous association between traffic-related air pollutant exposures and symptoms of current rhinitis. Importantly, the London LEZ has not significantly improved air quality within the city, or the respiratory health of the resident population in its first three years of operation. This highlights the need for more robust measures to reduce traffic emissions.

Physics-Informed Neural Network (PINN) has emerged as a promising tool for solving various physical problems with differential equations. However in practice, PINN often suffers from the local minima issue while solving problems with minimal initial conditions. In this paper, we propose a robust Gated-PINN to address this issue, which blends numerical methods and PINN. The Gated-PINN overcomes the local minima issue by controlling the flow of information of the neural network similar to a numerical method. We first investigate the use of conventional PINN to the Cartesian-coordinate simple pendulum problem with minimal initial conditions, as one of basic differential algebraic equation (DAE) problem. Our results show the advantage of PINN over existing numerical methods in that it does not require sophisticated mathematical techniques such as index reduction. But we also observe that conventional PINN can lead to inaccurate solutions; such solutions partially satisfy the differential equation requirement, but does not meet the given initial condition and fail to further improve. We demonstrate the effectiveness of the proposed Gated-PINN by showing that it yields accurate solutions, such that for a pendulum of length 1, the mean Euclidean error between the Gated-PINN model and the traditional numerical method model is less than 0.01 and pointwise maximum Euclidean error is less than 0.04. Moreover, Gated-PINN can operate without any complicated index reduction, and unlike conventional PINN, accurate solution can be obtained consistently without falling into a local minima. Overall, our study presents the potential of the Gated-PINN for solving DAE problems and provides a valuable insight into the challenges and limitations of using PINN for solving physical problems.

Introduction: In this study we aimed to investigate the prognostic accuracy for predicting in-hospital mortality using respiratory Sequential Organ Failure Assessment (SOFA) scores by the conventional method of missing-value imputation with normal partial pressure of oxygen (PaO2)- and oxygen saturation (SpO2)-based estimation methods. Methods: This was a single-center, retrospective cohort study of patients with suspected infection in the emergency department. The primary outcome was in-hospital mortality. We compared the area under the receiver operating characteristics curve (AUROC) and calibration results of the conventional method (normal value imputation for missing PaO2) and six SpO2-based methods: using methods A, B, PaO2 is estimated by dividing SpO2 by a scale; with methods C and D, PaO2 was estimated by a mathematical model from a previous study; with methods E, F, respiratory SOFA scores was estimated by SpO2 thresholds and respiratory support use; with methods A, C, E are SpO2-based estimation for all PaO2 values, while methods B, D, F use such estimation only for missing PaO2 values. Results: Among the 15,119 patients included in the study, the in-hospital mortality rate was 4.9%. The missing PaO2was 56.0%. The calibration plots were similar among all methods. Each method yielded AUROCs that ranged from 0.735–0.772. The AUROC for the conventional method was 0.755 (95% confidence interval [CI] 0.736–0.773). The AUROC for method C (0.772; 95% CI 0.754–0.790) was higher than that of the conventional method, which was an SpO2-based estimation for all PaO2 values. The AUROC for total SOFA score from method E (0.815; 95% CI 0.800–0.831) was higher than that from the conventional method (0.806; 95% CI 0.790–0.822), in which respiratory SOFA was calculated by the predefined SpO2 cut-offs and oxygen support. Conclusion: In non-ICU settings, respiratory SOFA scores estimated by SpO2 might have acceptable prognostic accuracy for predicting in-hospital mortality. Our results suggest that SpO2-based respiratory SOFA score calculation might be an alternative for evaluating respiratory organ failure in the ED and clinical research settings.

Currently, coating with anti-reflective materials is an attractive approach to improve the quality of screen-based displays. In this study, mesoporous silica particles were systematically synthesized as a function of surfactant (i.e., CTAC-cetyltrimethylammonium chloride) concentration to serve as main coating fillers possessing low refractive indices. Precisely changing the amount of the CTAC surfactant, silica sol with an average diameter of 50 nm exhibits distinctively different specific surface areas, pore size, and pore volume. Prior to the preparation of final coating solutions containing these silica particle fillers, the percentage of solid content was optimized on a glass slide. The use of 50 wt% solid content exhibited the highest transmittance of light. Among various content levels of silica sol, the use of 3.5 wt% of silica particles in the solid content displayed the highest transmittance (i.e., best anti-reflectiveness). Under the almost identical coating layers prepared with the fixed amount of silica particles possessing different surface areas, pore size, and pore volume, it appears that the largest pore volume played the most important role in improving the anti-reflective properties. Experimentally understanding the key feature of low-refractive filler materials under the optimized conditions could provide a clear view to develop highly effective anti-reflective materials for various display applications.

Due to growing concerns about environmental pollution from plastic waste, plastic recycling research is gaining momentum. Traditional methods, such as incorporating inorganic particles, increasing cross-linking density with peroxides, and blending with silicone monomers, often improve mechanical properties but reduce flexibility for specific performance requirements. This study focuses on synthesizing silica nanoparticles with vinyl functional groups and evaluating their mechanical performance when used in recycled plastics. Silica precursors, namely sodium silicate and vinyltrimethoxysilane (VTMS), combined with a surfactant, were employed to create pores, increasing silica’s surface area. The early-stage introduction of vinyl functional groups prevented the typical post-synthesis reduction in surface area. Porous silica was produced in varying quantities of VTMS, and the synthesized porous silica nanomaterials were incorporated into recycled polyethylene to induce cross-linking. Despite a decrease in surface area with increasing VTMS content, a significant surface area of 883 m2/g was achieved. In conclusion, porous silica with the right amount of vinyl content exhibited improved mechanical performance, including increased tensile strength, compared to conventional porous silica. This study shows that synthesized porous silica with integrated vinyl functional groups effectively enhances the performance of recycled plastics.

Background: Lactate is a commonly used biomarker for sepsis, although it has limitations in certain cases, suggesting the need for novel biomarkers. We evaluated the diagnostic accuracy of plasma renin concentration and renin activity for mortality and kidney outcomes in patients with sepsis with hypoperfusion or hypotension. Methods: This was a multicenter, prospective, observational study of 117 patients with septic shock treated at three tertiary emergency departments between September 2021 and October 2022. The accuracy of renin activity, renin, and lactate concentrations in predicting 28-day mortality, acute kidney injury (AKI), and renal replacement requirement was assessed using the area under the ROC curve (AUC) analysis. Results: The AUCs of initial renin activity, renin, and lactate concentrations for predicting 28-day mortality were 0.66 (95% confidence interval [CI], 0.55–0.77), 0.63 (95% CI, 0.52–0.75), and 0.65 (95% CI, 0.53–0.77), respectively, and those at 24 hrs were 0.74 (95% CI, 0.62–0.86), 0.70 (95% CI, 0.56–0.83), and 0.67 (95% CI, 0.54–0.79). Renin concentrations and renin activity outperformed initial lactate concentrations in predicting AKI within 14 days. The AUCs of renin and lactate concentrations were 0.71 (95% CI, 0.61–0.80) and 0.57 (95% CI, 0.46–0.67), respectively (P =0.030). The AUC of renin activity (0.70; 95% CI, 0.60–0.80) was also higher than that of lactate concentration (P =0.044). Conclusions: Renin concentration and renin activity show comparable performance to lactate concentration in predicting 28-day mortality in patients with septic shock but superior performance in predicting AKI. [ABSTRACT FROM AUTHOR]

Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks is associated with more extreme fluctuations in depression over time, rather than necessarily more severe depression. We gathered data from two independent samples of N = 155 paid students and N = 194 citizen scientists who rated their positive and negative emotions on a smartphone app twice a day and completed a weekly depression questionnaire for 8 wk. We constructed thousands of personalized emotion networks for each participant and tested whether connectivity was associated with severity of depression or its variance over 8 wk. Network connectivity was positively associated with baseline depression severity in citizen scientists, but not paid students. In contrast, 8-wk variance of depression was correlated with network connectivity in both samples. When controlling for depression variance, the association between connectivity and baseline depression severity in citizen scientists was no longer significant. We replicated these findings in an independent community sample (N = 519). We conclude that elevated network connectivity is associated with greater variability in depression symptoms. This variability only translates into increased severity in samples where depression is on average low and positively skewed, causing mean and variance to be more strongly correlated. These findings, although correlational, suggest that while emotional network connectivity could predispose individuals to severe depression, it could also be leveraged to bring about therapeutic improvements. [ABSTRACT FROM AUTHOR]

Introduction: In this study we aimed to investigate the prognostic accuracy for predicting in-hospital mortality using respiratory Sequential Organ Failure Assessment (SOFA) scores by the conventional method of missing-value imputation with normal partial pressure of oxygen (PaO2)- and oxygen saturation (SpO2)-based estimation methods. Methods: This was a single-center, retrospective cohort study of patients with suspected infection in the emergency department. The primary outcome was in-hospital mortality. We compared the area under the receiver operating characteristics curve (AUROC) and calibration results of the conventional method (normal value imputation for missing PaO2) and six SpO2-based methods: using methods A, B, PaO2 is estimated by dividing SpO2 by a scale; with methods C and D, PaO2 was estimated by a mathematical model from a previous study; with methods E, F, respiratory SOFA scores was estimated by SpO2 thresholds and respiratory support use; with methods A, C, E are SpO2-based estimation for all PaO2 values, while methods B, D, F use such estimation only for missing PaO2 values. Results: Among the 15,119 patients included in the study, the in-hospital mortality rate was 4.9%. The missing PaO2 was 56.0%. The calibration plots were similar among all methods. Each method yielded AUROCs that ranged from 0.735-0.772. The AUROC for the conventional method was 0.755 (95% confidence interval [CI] 0.736-0.773). The AUROC for method C (0.772; 95% CI 0.754-0.790) was higher than that of the conventional method, which was an SpO2-based estimation for all PaO2 values. The AUROC for total SOFA score from method E (0.815; 95% CI 0.800-0.831) was higher than that from the conventional method (0.806; 95% CI 0.790-0.822), in which respiratory SOFA was calculated by the predefined SpO2 cut-offs and oxygen support. Conclusion: In non-ICU settings, respiratory SOFA scores estimated by SpO2 might have acceptable prognostic accuracy for predicting in-hospital mortality. Our results suggest that SpO2-based respiratory SOFA score calculation might be an alternative for evaluating respiratory organ failure in the ED and clinical research settings. [ABSTRACT FROM AUTHOR]

Pancreatic pseudoaneurysm is a potentially life-threatening complication often associated with pancreatitis or pancreatic surgery. As the rupture of pancreatic pseudoaneurysms can lead to catastrophic bleeding and is associated with high mortality rates, clinical suspicion and early diagnosis are essential to improve patient outcomes. In the management of pseudoaneurysms, transarterial embolization (TAE) could be effective; however, there have been limited local studies on the outcomes of TAE for patients with pseudoaneurysm rupture associated with pancreatitis. Here, we describe patients who were diagnosed with pseudoaneruysm rupture associated with pancreatitis and treated with TAE. [ABSTRACT FROM AUTHOR]